Abstract

Employee resistance to AI persists even when infrastructure, training, and management support are in place. Existing frameworks such as Technology Acceptance Model explain acceptance of AI but not resistance. Our work integrates Protection Motivation Theory (PMT) (Rogers, 1975) and Technology Threat Avoidance Theory (TTAT) (Liang & Xue, 2010) to explain workplace AI resistance, with organizational culture and management support as key moderators. PMT posits that threat appraisal - perceived severity (fears of job displacement, skill obsolescence, privacy loss, and algorithmic distrust) and perceived vulnerability combined with low coping appraisal (response efficacy, self-efficacy, response costs) produces a maladaptive response - resistance. We operationalize AI resistance as avoidance (non-use), workarounds (parallel manual processes), and compliance theater (performing AI use while discarding outputs). TTAT states that at high threat levels, employees shift from problem-focused to emotion-focused coping -distancing, denial, rationalization, thereby weakening safeguard effectiveness-avoidance motivation link. In AI contexts, employees facing extreme displacement fear may disengage rather than adopt safeguards, meaning campaigns overemphasizing AI risk can backfire. Safeguard cost further predicts that learning burdens and accountability risks under opaque AI systems independently deter adoption. Organizational culture and management support moderate threat and coping appraisal. Innovation-driven cultures reduce response costs and elevate self-efficacy; hierarchical cultures amplify threat severity and inflate coping costs (Shokrollahi, 2025). Management support operates indirectly through trust - raising response efficacy and suppressing emotion-focused coping. Golgeci et al.'s process model explains the temporal arc: threat appraisal activates mistrust, existential questioning, and technological reflection, which AI legitimation mechanisms resolve over time (Golgeci, 2025). We propose a cross-sectional survey design analyzed using PLS-SEM. Contributions: (1) using PMT and TTAT to explain AI resistance and its emotion-focused coping dimension; (2) backfire risk of high-threat messaging; (3) culture and management support as coping appraisal moderators; and (4) connecting appraisal theory to dynamic resistance process.

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